The goal of the research was to improve software cost estimation by focusing on economic value. The researchers reviewed existing methods, tested new models with real project data, and found that a model based on input and output modules, tables, and algorithms had the best prediction accuracy. They collected data from 39 companies and found a strong correlation between function points and project effort. The revised technical complexity factors and guidelines were found to be practical and useful. Overall, the results suggest that incorporating these findings into software cost estimation guidelines can lead to faster technology innovation and increased productivity in the software industry.